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1,535 results on '"Lu, Jiwen"'

201. Graininess-Aware Deep Feature Learning for Pedestrian Detection

Author

Lin, Chunze, Lu, Jiwen, Wang, Gang, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Ferrari, Vittorio, editor, Hebert, Martial, editor, Sminchisescu, Cristian, editor, and Weiss, Yair, editor

Published
2018
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202. Deep Reinforcement Learning with Iterative Shift for Visual Tracking

Author

Ren, Liangliang, Yuan, Xin, Lu, Jiwen, Yang, Ming, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Ferrari, Vittorio, editor, Hebert, Martial, editor, Sminchisescu, Cristian, editor, and Weiss, Yair, editor

Published
2018
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203. Relaxation-Free Deep Hashing via Policy Gradient

Author

Yuan, Xin, Ren, Liangliang, Lu, Jiwen, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Ferrari, Vittorio, editor, Hebert, Martial, editor, Sminchisescu, Cristian, editor, and Weiss, Yair, editor

Published
2018
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204. Collaborative Deep Reinforcement Learning for Multi-object Tracking

Author

Ren, Liangliang, Lu, Jiwen, Wang, Zifeng, Tian, Qi, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Ferrari, Vittorio, editor, Hebert, Martial, editor, Sminchisescu, Cristian, editor, and Weiss, Yair, editor

Published
2018
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205. Part-Activated Deep Reinforcement Learning for Action Prediction

Author

Chen, Lei, Lu, Jiwen, Song, Zhanjie, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Ferrari, Vittorio, editor, Hebert, Martial, editor, Sminchisescu, Cristian, editor, and Weiss, Yair, editor

Published
2018
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206. Endo3D: Online Workflow Analysis for Endoscopic Surgeries Based on 3D CNN and LSTM

Author

Chen, Weixiang, Feng, Jianjiang, Lu, Jiwen, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Stoyanov, Danail, editor, Taylor, Zeike, editor, Sarikaya, Duygu, editor, McLeod, Jonathan, editor, González Ballester, Miguel Angel, editor, Codella, Noel C.F., editor, Martel, Anne, editor, Maier-Hein, Lena, editor, Malpani, Anand, editor, Zenati, Marco A., editor, De Ribaupierre, Sandrine, editor, Xiongbiao, Luo, editor, Collins, Toby, editor, Reichl, Tobias, editor, Drechsler, Klaus, editor, Erdt, Marius, editor, Linguraru, Marius George, editor, Oyarzun Laura, Cristina, editor, Shekhar, Raj, editor, Wesarg, Stefan, editor, Celebi, M. Emre, editor, Dana, Kristin, editor, and Halpern, Allan, editor

Published
2018
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207. Towards Accurate and Complete Registration of Coronary Arteries in CTA Images

Author

Zeng, Shaowen, Feng, Jianjiang, An, Yunqiang, Lu, Bin, Lu, Jiwen, Zhou, Jie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Frangi, Alejandro F., editor, Schnabel, Julia A., editor, Davatzikos, Christos, editor, Alberola-López, Carlos, editor, and Fichtinger, Gabor, editor

Published
2018
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208. Order-Sensitive Deep Hashing for Multimorbidity Medical Image Retrieval

Author

Chen, Zhixiang, Cai, Ruojin, Lu, Jiwen, Feng, Jianjiang, Zhou, Jie, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Frangi, Alejandro F., editor, Schnabel, Julia A., editor, Davatzikos, Christos, editor, Alberola-López, Carlos, editor, and Fichtinger, Gabor, editor

Published
2018
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225. Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks

Author

Liu, Honghui, Feng, Jianjiang, Feng, Zishun, Lu, Jiwen, Zhou, Jie, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Cardoso, M. Jorge, editor, Arbel, Tal, editor, Carneiro, Gustavo, editor, Syeda-Mahmood, Tanveer, editor, Tavares, João Manuel R.S., editor, Moradi, Mehdi, editor, Bradley, Andrew, editor, Greenspan, Hayit, editor, Papa, João Paulo, editor, Madabhushi, Anant, editor, Nascimento, Jacinto C., editor, Cardoso, Jaime S., editor, Belagiannis, Vasileios, editor, and Lu, Zhi, editor

Published
2017
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226. Left Atrial Appendage Segmentation Based on Ranking 2-D Segmentation Proposals

Author

Wang, Lei, Feng, Jianjiang, Jin, Cheng, Lu, Jiwen, Zhou, Jie, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Mansi, Tommaso, editor, McLeod, Kristin, editor, Pop, Mihaela, editor, Rhode, Kawal, editor, Sermesant, Maxime, editor, and Young, Alistair, editor

Published
2017
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244. Simultaneous Audio Source Localization and Microphone Placement

Author

Luo, Peng, Lu, Jiwen, Zhou, Jie, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Tan, Tieniu, editor, Li, Xuelong, editor, Chen, Xilin, editor, Zhou, Jie, editor, Yang, Jian, editor, and Cheng, Hong, editor

Published
2016
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245. Adaptive Multi-Agent Deep Mixed Reinforcement Learning for Traffic Light Control

Author

Li, Lulu, Zhu, Ruijie, Wu, Shuning, Ding, Wenting, Xu, Mingliang, and Lu, Jiwen

Abstract

Despite significant advancements in Multi-Agent Deep Reinforcement Learning (MADRL) approaches for Traffic Light Control (TLC), effectively coordinating agents in diverse traffic environments remains a challenge. Studies in MADRL for TLC often focus on repeatedly constructing the same intersection models with sparse experience. However, real road networks comprise Multi-Type of Intersections (MTIs) rather than being limited to intersections with four directions. In the scenario with MTIs, each type of intersection exhibits a distinctive topology structure and phase set, leading to disparities in the spaces of state and action. This article introduces Adaptive Multi-agent Deep Mixed Reinforcement Learning (AMDMRL) for addressing tasks with multiple types of intersections in TLC. AMDMRL adopts a two-level hierarchy, where high-level proxies guide low-level agents in decision-making and updating. All proxies are updated by value decomposition to obtain the globally optimal policy. Moreover, the AMDMRL approach incorporates a mixed cooperative mechanism to enhance cooperation among agents, which adopts a mixed encoder to aggregate the information from correlated agents. We conduct comparative experiments involving four traditional and four DRL-based approaches, utilizing three training and four testing datasets. The results indicate that the AMDMRL approach achieves average reductions of 41% than traditional approaches, and 16% compared to DRL-based approaches in traveling time on three training datasets. During testing, the AMDMRL approach exhibits a 37% improvement in reward compared to the MADRL-based approaches.

Published
2024
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246. Back to Reality: Learning Data-Efficient 3D Object Detector With Shape Guidance

Author

Xu, Xiuwei, Wang, Ziwei, Zhou, Jie, and Lu, Jiwen

Abstract

In this paper, we propose a weakly-supervised approach for 3D object detection, which makes it possible to train a strong 3D detector with position-level annotations (i.e. annotations of object centers and categories). In order to remedy the information loss from box annotations to centers, our method makes use of synthetic 3D shapes to convert the position-level annotations into virtual scenes with box-level annotations, and in turn utilizes the fully-annotated virtual scenes to complement the real labels. Specifically, we first present a shape-guided label-enhancement method, which assembles 3D shapes into physically reasonable virtual scenes according to the coarse scene layout extracted from position-level annotations. Then we transfer the information contained in the virtual scenes back to real ones by applying a virtual-to-real domain adaptation method, which refines the annotated object centers and additionally supervises the training of detector with the virtual scenes. Since the shape-guided label enhancement method generates virtual scenes by human-heuristic physical constraints, the layout of the fixed virtual scenes may be unreasonable with varied object combinations. To address this, we further present differentiable label enhancement to optimize the virtual scenes including object scales, orientations and locations in a data-driven manner. Moreover, we further propose a label-assisted self-training strategy to fully exploit the capability of detector. By reusing the position-level annotations and virtual scenes, we fuse the information from both domains and generate box-level pseudo labels on the real scenes, which enables us to directly train a detector in fully-supervised manner. Extensive experiments on the widely used ScanNet and Matterport3D datasets show that our approach surpasses current weakly-supervised and semi-supervised methods by a large margin, and achieves comparable detection performance with some popular fully-supervised methods with less than 5% of the labeling labor.

Published
2024
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